Knowledge-based (KB) technology is being applied to complex problem-solving and critical tasks in many application domains. Concerns have naturally arisen as to the dependability of knowledge-based systems (KBS). As with any software, attention to quality and safety must be paid throughout development of a KBS and rigorous verification and validation (V&V) techniques must be employed. Research in V&V of KBS has emerged as a distinct field only in the last decade and is intended to address issues associated with quality and safety aspects of KBS and to credit such applications with the same degree of dependability as conventional applications. In recent years, V&V of KBS has been the topic of annual workshops associated with the main AI conferences, such as AAAI, IJACI and ECAI. Validation and Verification of Knowledge Based Systems contains a collection of papers, dealing with all aspects of KBS V&V, presented at the Fifth European Symposium on Verification and Validation of Knowledge Based Systems and Components (EUROVAV'99 - which was held in Oslo in the summer of 1999, and was sponsored by Det Norske Veritas and the British Computer Society's Specialist Group on Expert Systems (SGES).

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The book presents state of the art practices and research in the area of Knowledge Capture and Reuse in industry. This book demonstrates some of the successful applications of industrial knowledge management at the micro level. The Micro Knowledge Management (MicroKM) is about capture and reuse of knowledge at the operational, shopfloor and designer level. The readers will benefit from different frameworks, concepts and industrial case studies on knowledge capture and reuse. The book contains a number of invited papers from leading practitioners in the field and a small number of selected papers from active researchers. The book starts by providing the foundation for micro knowledge management through knowledge systematisation, analysing the nature of knowledge and by evaluating verification and validation technology for knowledge based system of frameworks for knowledge capture, reuse and development. A number integration are also provided. Web based framework for knowledge capture and delivery is becoming increasingly popular. Evolutionary computing is also used to automate design knowledge capture. The book demonstrates frameworks and techniques to capture knowledge from people, data and process and reuse the knowledge using an appropriate tool in the business. Therefore, the book bridges the gap between the theory and practice. The 'theory to practice' chapter discusses about virtual communities of practice, Web based approaches, case based reasoning and ontology driven systems for the knowledge management. Just-in-time knowledge delivery and support is becoming a very important tool for real-life applications.

The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making.With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.

Knowledge-based systems are increasingly found in a wide variety of settings and this handbook has been written to meet a specific need in their widening use. While there have been many successful applications of knowledge-based systems, some applications have failed because they never received the corrective feedback that evaluation provides for keeping development focused on the users' needs in their actual working environment. This handbook provides a conceptual framework and compendium of methods for performing evaluations of knowledge-based systems during their development. Its focus is on the users' and subject matter experts' evaluation of the usefulness of the system, and not on the developers' testing of the adequacy of the programming code. The handbook permits evaluators to systematically answer the following kinds of questions: Does the knowledge-based system meet the users' task requirements? Is the system easy to use? Is the knowledge base logically consistent? Does it meet the required level of expertise? Does the system improve performance? The authors have produced a handbook that will serve two audiences: a tool that can be used to create knowledge-based systems (practitioners, developers, and evaluators) and a framework that will stimulate more research in the area (academic researchers and students). To accomplish this, the handbook is built around a conceptual framework that integrates the different types of evaluations into the system of development process. The kinds of questions that can be answered, and the methods available for answering them, will change throughout the system development life cycle. And throughout this process, one needs to know what can be done, and what can't. It is this dichotomy that addresses needs in both the practitioner and academic research audiences.

Validation, Verification and Testing (VVT) are important and difficult to achieve for any software product--Knowledge-Based Systems (KBS) present particular problems, dealing as they do in probabilities, uncertainties and approximations. This collection of papers looks at current research and implementation issues; describes tools, techniques and validation and verification criteria; discusses particular projects; and includes a survey of developers.

This collection of previously published papers brings together state-of-the-art developments in expert system testing. The volume is separated into five chapters on expert system validation, knowledge base verification, development and evaluation, case studies and tools, and general topics. The pape

Knowledge Based Systems (KBS) are systems that use artificial intelligence techniques in the problem solving process. This text is designed to develop an appreciation of KBS and their architecture and to help users understand a broad variety of knowledge based techniques for decision support and planning. It assumes basic computer science skills and a math background that includes set theory, relations, elementary probability, and introductory concepts of artificial intelligence. Each of the 12 chapters are designed to be modular providing instructors with the flexibility to model the book to their own course needs. Exercises are incorporated throughout the text to highlight certain aspects of the material being presented and to stimulate thought and discussion.

We never create anything, We discover and reproduce. The Twelfth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems has a distinguished theme. It is concerned with bridging the gap between the academic and the industrial worlds of Artificial Intelligence (AI) and Expert Systems. The academic world is mainly concerned with discovering new algorithms, approaches, and methodologies; however, the industrial world is mainly driven by profits, and concerned with producing new products or solving customers’ problems. Ten years ago, the artificial intelligence research gap between academia and industry was very broad. Recently, this gap has been narrowed by the emergence of new fields and new joint research strategies in academia. Among the new fields which contributed to the academic-industrial convergence are knowledge representation, machine learning, searching, reasoning, distributed AI, neural networks, data mining, intelligent agents, robotics, pattern recognition, vision, applications of expert systems, and others. It is worth noting that the end results of research in these fields are usually products rather than empirical analyses and theoretical proofs. Applications of such technologies have found great success in many domains including fraud detection, internet service, banking, credit risk and assessment, telecommunication, etc. Progress in these areas has encouraged the leading corporations to institute research funding programs for academic institutes. Others have their own research laboratories, some of which produce state of the art research.

Systems' Verification Validation and Testing (VVT) are carried out throughout systems' lifetimes. Notably, quality-cost expended on performing VVT activities and correcting system defects consumes about half of the overall engineering cost. Verification, Validation and Testing of Engineered Systems provides a comprehensive compendium of VVT activities and corresponding VVT methods for implementation throughout the entire lifecycle of an engineered system. In addition, the book strives to alleviate the fundamental testing conundrum, namely: What should be tested? How should one test? When should one test? And, when should one stop testing? In other words, how should one select a VVT strategy and how it be optimized? The book is organized in three parts: The first part provides introductory material about systems and VVT concepts. This part presents a comprehensive explanation of the role of VVT in the process of engineered systems (Chapter-1). The second part describes 40 systems' development VVT activities (Chapter-2) and 27 systems' post-development activities (Chapter-3). Corresponding to these activities, this part also describes 17 non-testing systems' VVT methods (Chapter-4) and 33 testing systems' methods (Chapter-5). The third part of the book describes ways to model systems' quality cost, time and risk (Chapter-6), as well as ways to acquire quality data and optimize the VVT strategy in the face of funding, time and other resource limitations as well as different business objectives (Chapter-7). Finally, this part describes the methodology used to validate the quality model along with a case study describing a system's quality improvements (Chapter-8). Fundamentally, this book is written with two categories of audience in mind. The first category is composed of VVT practitioners, including Systems, Test, Production and Maintenance engineers as well as first and second line managers. The second category is composed of students and faculties of Systems, Electrical, Aerospace, Mechanical and Industrial Engineering schools. This book may be fully covered in two to three graduate level semesters; although parts of the book may be covered in one semester. University instructors will most likely use the book to provide engineering students with knowledge about VVT, as well as to give students an introduction to formal modeling and optimization of VVT strategy.